A Technique for Computerised Brushwork Analysis

@inproceedings{Murashov2015ATF,
  title={A Technique for Computerised Brushwork Analysis},
  author={Dmitry M. Murashov and Alexey Berezin and Ekaterina Yu. Ivanova},
  booktitle={VISAPP},
  year={2015}
}
In this work, the problem of computer-assisted attribution of fine-art paintings based on image analysis methods is considered. A technique for comparing artistic styles is proposed. Textural features represented by histograms of brushstroke ridge orientation and local neighborhood orientation are used in this work to characterize painter's artistic style. The procedures for feature extraction are developed and the parameters are chosen. The paintings are compared using three informative… 
2 Citations

Figures from this paper

Application of texture features for comparing the facture of paintings
  • D. Murashov
  • Art
    Pattern Recognition and Image Analysis
  • 2016
The paper continues investigations on the development of a computer-aided method for the analysis of images of the facture of pictorial artworks. The feature description of the facture of paintings
Feature description of informative fragments in the problem of computerized attribution of paintings
  • D. Murashov
  • Computer Science
    Pattern Recognition and Image Analysis
  • 2015
TLDR
A feature description of a facture of paintings based on the characteristics of a grayscale image relief and elements of the structure tensor is proposed, which is a quantitative characteristic of the artistic style of an author.

References

SHOWING 1-10 OF 17 REFERENCES
Structural analysis of paintings based on brush strokes
The origin of works of art can often not be attributed to a certain artist. Likewise it is difficult to say whether paintings or drawings are originals or forgeries. In various fields of art new
Image processing for artist identification
TLDR
The approaches to brushwork analysis and artist identification developed by three research groups are described within the framework of this data set of 101 high-resolution gray-scale scans of paintings within the Van Gogh and Kroller-Muller museums.
Texture Analysis for Stroke Classification in Infrared Reflectogramms
TLDR
The method uses texture analysis algorithms performing along the drawing trace to distinguish between different types of strokes and the benefit is the increased content of textural information within the stroke and simultaneously in the border region.
Recovering layers of brush strokes through statistical analysis of color and shape: an application to van Gogh's Self portrait with grey felt hat
TLDR
Digital image processing and statistical clustering algorithms are used to segment and classify brush strokes in master paintings based on two-dimensional space and three-dimensional chromaticity coordinates to aid art scholars in characterizing the images of paintings as well as the working methods of some master painters.
Detection of forgery in paintings using supervised learning
TLDR
It is demonstrated that supervised machine learning on features derived from hidden-Markov-tree-modeling of the paintings' wavelet coefficients has the potential to distinguish copies from originals in the new dataset.
Rhythmic Brushstrokes Distinguish van Gogh from His Contemporaries: Findings via Automated Brushstroke Extraction
TLDR
It is confirmed that the combined brushwork features identified as special to van Gogh are consistently held throughout his French periods of production (1886-1890).
Localization of differences between multimodal images on the basis of an information-theoretical measure
  • D. Murashov
  • Computer Science
    Pattern Recognition and Image Analysis
  • 2014
The problem of the localization of image artifacts obtained in different spectral ranges on the basis of an information-theoretical difference measure is considered. Use of the conditional entropy
Information Theory in Computer Vision and Pattern Recognition
TLDR
This book explores and introduces information theory elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented, seeking a comprehensive research roadmap.
Digital Image Processing
TLDR
This paper explains what is imageprocessing, types, digital image processing, and also the history, tasks and applications of it.
Ridges in Image and Data Analysis
  • D. Eberly
  • Mathematics
    Computational Imaging and Vision
  • 1996
TLDR
This book discussesidges in Euclidean Geometry, a model of geometry based on the model of Riemannian geometry, and applications to Image and Data Analysis.
...
...